# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Generates a toy v1 saved model for testing."""

import shutil
from absl import app
from absl import flags
from tensorflow.python.client import session
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import parsing_ops
from tensorflow.python.saved_model import builder
from tensorflow.python.saved_model import signature_constants
from tensorflow.python.saved_model import signature_def_utils
from tensorflow.python.saved_model import tag_constants
from tensorflow.python.saved_model import utils

flags.DEFINE_string('saved_model_path', '', 'Path to save the model to.')
FLAGS = flags.FLAGS


def main(argv):
  if len(argv) > 1:
    raise app.UsageError('Too many command-line arguments.')

  ops.disable_eager_execution()
  shutil.rmtree(FLAGS.saved_model_path)

  # Create the graph
  x = array_ops.placeholder(dtypes.string, shape=(1), name='input')
  features = {
      'key': parsing_ops.FixedLenFeature([], dtypes.int64, default_value=0)
  }
  parsed_features = parsing_ops.parse_example(x, features)
  r = parsed_features['key']

  sess = session.Session()

  sm_builder = builder.SavedModelBuilder(FLAGS.saved_model_path)
  tensor_info_x = utils.build_tensor_info(x)
  tensor_info_r = utils.build_tensor_info(r)

  toy_signature = (
      signature_def_utils.build_signature_def(
          inputs={'x': tensor_info_x},
          outputs={'r': tensor_info_r},
          method_name=signature_constants.PREDICT_METHOD_NAME))

  sm_builder.add_meta_graph_and_variables(
      sess, [tag_constants.SERVING],
      signature_def_map={
          signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY: toy_signature,
      },
      strip_default_attrs=True)
  sm_builder.save()


if __name__ == '__main__':
  app.run(main)
